Online ISSN: 2515-8260

Keywords : python

Clustering Analysis from Universities in Indonesia based on Sentiment Analysis

Hendra Achmadi; Isana Meranga; Dewi Wuisan; Irwan Suarly; I Gusti Anom Yudistira; Rudy Pramono

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 10, Pages 1466-1481

There are two kind of source to determine the quality for a good university in Indonesia. First from university cluster which is publish from Ministry of Research, Technology and Higher Education issued a clustering list of Indonesian universities, the second source of data from social media, such as Twitter. In this research we use Text Mining and Data Mining Methodology to build a sentiment analysis from 50100 Tweet to assess 501 university using Python and special library in Python for Natural Language Processing a sentiment analysis , which is join the university clustering from Ministry of Research, Technology and Higher Education, so it will produce the positive, neutral and negative sentiment for each 501 universities in 2020. The next process by using R STUDIO, the process classification is continued by using K-Means, the process can be devided into two step , step 1 it will process 501 dataset university and it will build 5 cluster and secondly the similarities between Netizen cluster and cluster from Ministry of Research, Technology and Higher Education is 37 %, and step 2 after cleansing the 0 value, the result is 169 universites the similarities between Netizen cluster and cluster from Ministry of Research, Technology and Higher Education is 37 % before and after data cleansing was the same. The novelty knowledge or research finding can be derived from Netizen, firstly, the cluster can be derived based on Positive Sentiment,. Secondly, the cluster from Netizen and Cluster from Directorate General of Higher Education, Ministry of Education and Culture of higher education in Indonesia is only match around 37 % with cluster form Directorate General of Higher Education. And after data cleansing from 169 university was only match around 33 %..

Use of AI Based “CHATBOTS” for Providing Health Related Information

M.I. Anju; T. Saravanan; P.Calista Bebe; M.Sherly Deva Kirubai

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 11, Pages 7698-7706

To have a decent existence, medical care is a lot of significant. Be it as it may, if there should be a case with any medical issues, it is difficult to obtain the counsel with the expert. The suggested idea is to use Artificial Intelligence to create a clinical chatbot that can evaluate the illness and provide critical insights about the infection before counselling a specialist. To diminish the medical services costs and improve openness to clinical information the clinical chatbot is constructed. Some chatbots are used as clinical reference books, which enable the patient to find out about their disease and help improve their well-being.The client can accomplish the genuine advantage of a chatbot just when it can analyse all sort of malady and give vital data. A book to-message analysis bot draws in patients in discussion about their clinical issues and gives a customized determination dependent on their manifestations. Henceforth, individuals will have a thought regarding their wellbeing and have the correct assurance.



European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2668-2680

Documents of the ancient time gift several opposition for standalone gesture recognition systems, among them, the division and classification steps. Fastidiously gloss wordings square measure is required to coach a system. In some eventualities, written document square measure solely offered at the subdivision level. During this activity, we have a tendency to demonstrate the way to train the system with few tagged information. We have a tendency to additionally propose a model-based social control theme that considers the variability within the writing scale at the popularity section. We have a tendency to apply this approach to the publically offered browse dataset. Our system achieved the competitor result. Humans have distinctive handwriting designs that prove to be an obstacle for handwriting recognition algorithms. To date, multiple researches are done to acknowledge these totally different handwriting designs, most notable mistreatment the synthetic neural network (ANN) with back propagation algorithms that has additionally been verified to relinquish adequately high accuracies. By mistreatment real time method image capturing, this technique and algorithmic rule will be enforced to use multiple written entry information for faculties and universities, wherever the written information of a regular score sheet from totally different people will be transferred to a computer program.

Smart Mall Parking Management System Using Image Processing

Kanaga Suba Raja. S; Usha Kiruthika; R. Jaichandran; Balaji . V; Rameshwer . S; Roheeth. S

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 3004-3010

In India, the existing parking lot systems requires the car drivers looking for empty parking slots
within the car parking without providing any sort of detailed directions toward the available parking
spaces. As a result, drivers tend to waste tons of their time and energy whilst having to navigate through the
parking spaces within the car parking without knowing the right direction which would simply cause traffic
congestions within. This paper looks into this issue of car parking system in India and eventually proposes
an Android-based Car Parking System using low cost Image-Processing. The implementation of Image-
Processing into the car parking system enables drivers to receive data on the of empty car parking spaces.
The paper sets out to present an intelligent parking management system for empty parking zone detection
supported by image processing techniques, that captures and processes the image drawn at parking lot and
produces the space of the empty car parking spaces. This paper works on the planning and implementation
of Android-based Mall Parking that uses Image-Processing of the parking lot captured in frames from the
parking lot’s CCTV footage, finding the closest parking lot for drivers.

Crop Value Forecasting using Decision Tree Regressor and Model s

AkshayPrassanna S; B A Harshanand, B Srishti; Chaitanya R; KirubakaranNithiyaSoundari .; SwathiSriram .; V Manoj Kumar; VarshithaChennamsetti .; Venkateshwaran G; Dr.Pramod Kumar Maurya

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 2, Pages 3702-32722

Machine Learning is an emerging research field which can be used for the analysis of crop
price prediction and accurately provide solutions for the same. We can use this system as a backhand
while we decide what a farmer should plant while considering factors such as annual rainfall, WPI
and so on which is provided from the dataset and produce a logical conclusion on which products
would give a more reliable outcome. The performance between Random forest ensemble learning and
decision tree regressor is compared and it has been observed that the Random Forest Ensemble
learning method gives a higher accuracy. In this system there are 23 crops whose information can be
accessed upon for deciding collaborated with a simple user friendly UI

Text Mining Based on Tax Comments as Big Data Analysis Using XGBOOST and Feature Selection


European Journal of Molecular & Clinical Medicine, 2017, Volume 4, Issue 1, Pages 150-157

With the quick improvement of the Internet, enormous information has been applied in a lot of use.
Be that as it may, there are regularly excess or unessential highlights in high dimensional information, so
include determination is especially significant. By building subsets with new highlights and utilizing AI
calculations including Xgboost and so on. To acquire early notice data with high dependability and constant by
applying large information hypothesis, systems, models and techniques just as AI strategies are the unavoidable
patterns later on. this examination proposed the fast choice of highlights by utilizing XGboost model in dispersed
circumstances can improve the Model preparing proficiency under conveyed condition.
GBTs model dependent on the inclination streamlining choice tree was superior to the next two models as far as
precision and continuous execution, which meets the necessities under the large information foundation. It runs
on a solitary machine, just as the conveyed preparing structures Apache Hadoop, Apache Spark.
We can utilize inclination plummet for our slope boosting model. On account of a relapse tree, leaf hubs produce
a normal inclination among tests with comparative highlights. Highlight determination is a basic advance in
information preprocessing and significant research content in information mining and AI assignments, for
example, order.